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Stochastic Volatility, Trading Volume, and the Daily Flow of Information

  • Jeff Fleming

    (Rice University)

  • Chris Kirby

    (Clemson University)

  • Barbara Ostdiek

    (Rice University)

We use state-space methods to investigate the relation between volume, volatility, and ARCH effects within a mixture of distributions hypothesis (MDH) framework. Most recent studies of the MDH fit AR(1) specifications that require the information flow to be highly persistent. Using a more general specification, we find evidence of a large nonpersistent component of volatility that is closely related to the contemporaneous nonpersistent component of volume. However, in contrast to studies that fit volume-augmented GARCH models, we find no evidence that volume subsumes ARCH effects. Since volume-augmented GARCH models are subject to simultaneity bias, our findings should be more robust than these prior results.

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Article provided by University of Chicago Press in its journal Journal of Business.

Volume (Year): 79 (2006)
Issue (Month): 3 (May)
Pages: 1551-1590

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Handle: RePEc:ucp:jnlbus:v:79:y:2006:i:3:p:1551-1590
Contact details of provider: Web page: http://www.journals.uchicago.edu/JB/

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  11. Chib, Siddhartha & Nardari, Federico & Shephard, Neil, 2002. "Markov chain Monte Carlo methods for stochastic volatility models," Journal of Econometrics, Elsevier, vol. 108(2), pages 281-316, June.
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  17. Liesenfeld, Roman, 1998. "Dynamic Bivariate Mixture Models: Modeling the Behavior of Prices and Trading Volume," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(1), pages 101-09, January.
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